z71962
New member
- Joined
- Dec 21, 2019
- Member Type
- Student or Learner
- Native Language
- Chinese
- Home Country
- China
- Current Location
- China
Hi everyone,
Can you please review my SOP for master study in the US? I'm applying to Business Analytics Programs.
I really appreciate your effort.
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Along with the financial institutions like Citi and Morgan Stanley speed up to develop technical field in their businesses, the trend of combining finance and new technology seems unstoppable. One of the most prevalent applications is to apply machine learning into financial markets. As I probed into this area, I found it fascinating in its ability to make precise predictions and I believe that machine learning will play more important roles in finance in the future. This exciting trend drives me to devote myself into this area and this is my reason to apply for [program name].
As a student majoring in International Economics and Trade, I prepared myself from the choice of my courses, such as ODE, PDE, Probability and Statistics to enhance my mathematical background. Besides, I am also aware of the importance of coding in financial engineering area, and therefore I spared no effort learning programming languages such as Python, SQL and STATA.
In particular, what intrigued me the most was Python. I first encountered Python on Relationship between Financial Markets and FDI as an assistant researcher of Professor XXX at XXX University. I combined my data processing knowledge with statistical yearbook to process a giant amount of data base by using Python. Finally, a report about the 27-country FDI in recent six years was issued.
In the year of sophomore, I set up a research group entitled "Relationship between China's Import Diversification and its Export Technology Intensity". In the course of studying this topic, I self-learned the econometric programming software Stata, and used it to process the raw data into a visualized Chinese import diversification index and export technology intensity index, and found their positive correlation. This experience offered me an opportunity to further explore data analysis.
In addition, to exercise my mathematical modeling skills and improve the understanding of data analysis, I also participated in the 2018 Mathematical Contest in Modeling and built a model of languages to predict their development in the future.
These successful experiences in programming gave me confidence that applying programming and math methods into financial area was well worth doing. Thus, I did a one-year exchange to YYY University. I wanted to acquire more advanced knowledge of math and statistics. Therefore, I deliberately took two PhD level courses, which were Econometrics A and Econometrics B. In these two courses, I not only gained lots of statistics knowledge and learned about different mathematical models and measurement theories, but also formally and systematically learned applying Python in data visualization, data analyzing and model building. Although PhD courses were normally difficult for undergraduates, I received A and A+ as the pay-off of my hard work.
To better understand quant research and apply what I have learnt, I did an internship at XXX Securities, a famous securities company in China. I made a contribution to analyzing the PTA industry chain a type of chemical industry by using Python, Excel and such statistical programming software to analyze the macro and micro data of this industry. At the start of my internship, I did not have much background knowledge about the chemical industry as I was not majoring in chemical engineering, so I added relevant knowledge in time by doing a lot of paperwork. Soon, I mastered PTA industry chain production principles and market conditions. Then, my Python experience from YYY University became a useful tool to organize the statistics of various enterprises and prepare the research report.
Last but not least, I took part in a research project, Application of Artificial Intelligence in Quantitative Finance, which was held by a PhD candidate of ZZZ University. The goal of this project was to use the market data of the constituent stocks of the CSI 300 index to construct a multi-factor quantitative stock selection model and try to build a portfolio that outperforms the market. As the team-leader, I mainly focused on data preprocessing, single factor analyzing, calculation of correlation coefficients and construction of multi-factor models. During the process, Python and some other programming software were used to group and classify factors and further reduce the number of factors. Then a multi-factor model was constructed by regression. Finally, we used volatility to evaluate the model. This quantitative finance project gave me a deeper understanding of data analysis and statistics and its application in finance, and gave me further practical experience, which greatly stimulated my interest and enthusiasm for this.
These valuable opportunities helped me confirm my career goal to combine programming and math methods with finance area. After graduating from your program, I envision myself pursuing a research position in a securities company focusing on data analytics or quantitative finance. Both of these two areas provide a lot of opportunities to apply programming methods. As for my professional goal in a longer term, I plan to go back to China to start up my own firm, concentrating on helping financial institutions to reduce transaction costs using my prediction models. Quantitative finance is taking off in China, and there are many open opportunities. After establishing myself as an experienced researcher in this area, Im passionate about joining this trend and leading the development of this area. Therefore, I can do my best to enhance the technical development of Chinese financial sector, make the Chinese market integrate into the international market with a more open level, and promote the establishment of a globalized international financial market.
I regard the [program name] as the best choice for me for multiple reasons. Your comprehensive curriculum perfectly aligns with my career goal. Your course structure will perfectly help me to complete my knowledge system. Moreover, Im impressed at how your program helps students drive career success. Many professors brought on board from industry will help us better connect to real-world businesses. The great location in [city name] makes it more convenient for me to find an intern opportunity in finance area which will definitely help me to start my career in China.
For all such above, I believe that the [program name] will help me prepare myself for a quant researcher role and achieve my goal to applying machine learning methods into finance area. I am looking forward to studying in your program starting in Fall 2020.
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I think that this SOP is a bit longer (more than 1000 words), but I don't know how to shorten it. Besides, there might be some unnatural expressions. Please correct it. Thank you!
Can you please review my SOP for master study in the US? I'm applying to Business Analytics Programs.
I really appreciate your effort.
------------------------------------------------------------------------------------------------------------------------
Along with the financial institutions like Citi and Morgan Stanley speed up to develop technical field in their businesses, the trend of combining finance and new technology seems unstoppable. One of the most prevalent applications is to apply machine learning into financial markets. As I probed into this area, I found it fascinating in its ability to make precise predictions and I believe that machine learning will play more important roles in finance in the future. This exciting trend drives me to devote myself into this area and this is my reason to apply for [program name].
As a student majoring in International Economics and Trade, I prepared myself from the choice of my courses, such as ODE, PDE, Probability and Statistics to enhance my mathematical background. Besides, I am also aware of the importance of coding in financial engineering area, and therefore I spared no effort learning programming languages such as Python, SQL and STATA.
In particular, what intrigued me the most was Python. I first encountered Python on Relationship between Financial Markets and FDI as an assistant researcher of Professor XXX at XXX University. I combined my data processing knowledge with statistical yearbook to process a giant amount of data base by using Python. Finally, a report about the 27-country FDI in recent six years was issued.
In the year of sophomore, I set up a research group entitled "Relationship between China's Import Diversification and its Export Technology Intensity". In the course of studying this topic, I self-learned the econometric programming software Stata, and used it to process the raw data into a visualized Chinese import diversification index and export technology intensity index, and found their positive correlation. This experience offered me an opportunity to further explore data analysis.
In addition, to exercise my mathematical modeling skills and improve the understanding of data analysis, I also participated in the 2018 Mathematical Contest in Modeling and built a model of languages to predict their development in the future.
These successful experiences in programming gave me confidence that applying programming and math methods into financial area was well worth doing. Thus, I did a one-year exchange to YYY University. I wanted to acquire more advanced knowledge of math and statistics. Therefore, I deliberately took two PhD level courses, which were Econometrics A and Econometrics B. In these two courses, I not only gained lots of statistics knowledge and learned about different mathematical models and measurement theories, but also formally and systematically learned applying Python in data visualization, data analyzing and model building. Although PhD courses were normally difficult for undergraduates, I received A and A+ as the pay-off of my hard work.
To better understand quant research and apply what I have learnt, I did an internship at XXX Securities, a famous securities company in China. I made a contribution to analyzing the PTA industry chain a type of chemical industry by using Python, Excel and such statistical programming software to analyze the macro and micro data of this industry. At the start of my internship, I did not have much background knowledge about the chemical industry as I was not majoring in chemical engineering, so I added relevant knowledge in time by doing a lot of paperwork. Soon, I mastered PTA industry chain production principles and market conditions. Then, my Python experience from YYY University became a useful tool to organize the statistics of various enterprises and prepare the research report.
Last but not least, I took part in a research project, Application of Artificial Intelligence in Quantitative Finance, which was held by a PhD candidate of ZZZ University. The goal of this project was to use the market data of the constituent stocks of the CSI 300 index to construct a multi-factor quantitative stock selection model and try to build a portfolio that outperforms the market. As the team-leader, I mainly focused on data preprocessing, single factor analyzing, calculation of correlation coefficients and construction of multi-factor models. During the process, Python and some other programming software were used to group and classify factors and further reduce the number of factors. Then a multi-factor model was constructed by regression. Finally, we used volatility to evaluate the model. This quantitative finance project gave me a deeper understanding of data analysis and statistics and its application in finance, and gave me further practical experience, which greatly stimulated my interest and enthusiasm for this.
These valuable opportunities helped me confirm my career goal to combine programming and math methods with finance area. After graduating from your program, I envision myself pursuing a research position in a securities company focusing on data analytics or quantitative finance. Both of these two areas provide a lot of opportunities to apply programming methods. As for my professional goal in a longer term, I plan to go back to China to start up my own firm, concentrating on helping financial institutions to reduce transaction costs using my prediction models. Quantitative finance is taking off in China, and there are many open opportunities. After establishing myself as an experienced researcher in this area, Im passionate about joining this trend and leading the development of this area. Therefore, I can do my best to enhance the technical development of Chinese financial sector, make the Chinese market integrate into the international market with a more open level, and promote the establishment of a globalized international financial market.
I regard the [program name] as the best choice for me for multiple reasons. Your comprehensive curriculum perfectly aligns with my career goal. Your course structure will perfectly help me to complete my knowledge system. Moreover, Im impressed at how your program helps students drive career success. Many professors brought on board from industry will help us better connect to real-world businesses. The great location in [city name] makes it more convenient for me to find an intern opportunity in finance area which will definitely help me to start my career in China.
For all such above, I believe that the [program name] will help me prepare myself for a quant researcher role and achieve my goal to applying machine learning methods into finance area. I am looking forward to studying in your program starting in Fall 2020.
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I think that this SOP is a bit longer (more than 1000 words), but I don't know how to shorten it. Besides, there might be some unnatural expressions. Please correct it. Thank you!
